Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Connected and Autonomous Vehicles (CAVs) technology has the potential to transform the transportation system. Although these new technologies have many advantages, the implementation raises significant concerns regarding safety, security, and privacy. Anomalies in sensor data caused by errors or cyb...

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Bibliographic Details
Main Authors: Boyu Wang, Wan Li, Zulqarnain H. Khattak
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Electronics
Subjects:
cybersecurity
anomaly detection
falsified trajectories
CAVs
LSTM
Gaussian Mixture Model
Online Access:https://www.mdpi.com/2079-9292/13/7/1251

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https://www.mdpi.com/2079-9292/13/7/1251

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